Negative Effects of Event Sponsoring and Ambushing: the Case of Consumer Confusion

“Negative Effects of Event Sponsoring and Ambushing: The Case of Consumer Confusion”

Manuela Sachse, Chemnitz University of Technology

Jan Drengner, Chemnitz University of Technology

Steffen Jahn, Chemnitz University of Technology

Event sponsorship is one important marketing tool for companies to favorably influence brand awareness, attitudes or purchase intention. Since numerous sponsors use different leveraging techniques to promote their event engagement, these companies create a cluttered environment (Cornwell et al. 2000; Séguin and O’Reilly 2008). In the case of major events, this effect will be increased by several ambushers thatactively try to confuse people about who is official sponsor of an event and who is not (Dalakas, Madrigal, and Burton 2004). As a result, memory for sponsors might be reduced, diminishing the goal of awareness enhancement (Cornwell et al. 2006; Johar and Pham 1999). Such a consumer failure to develop a correct interpretation of various facets of a stimulus during the information processing procedure has been described as consumer confusion (Turnbull, Leek, and Ying 2000). The aim of the present study is to develop a theoretically sound conceptualization of consumer confusion and relate it to dark-side effects of sponsorship.

Drawing on Turnbull et al. (2000), we define consumer confusion as interfered information processing which impedes consumers’ ability to select and interpret relevant stimuli. We argue that this ‘core’ of the construct should be separated from the following antecedents (Mitchell and Papavassiliou 1999; Mitchell, Walsh and Yamin 2005):

-Perceived stimuli overload,resulting from the accumulated effects of many messages by a large number of sponsors and ambushers during an event.

-Perceived stimuli similarity, evolving from sponsors’ and ambushers’similar communication content and formal similarity (e.g., slogan, pictures), especially in situations of high similarity of the advertised products.

-Perceived stimuli ambiguity asambiguous, misleading, inadequate, and conflicting information,reflectinga typical side effect in information-rich environments (e.g., different sponsor categories during mega sports events).

Consequently, we derive a first set of hypotheses to test this conceptualization.

H1a: The higher the stimuli ambiguity, the higher the consumer confusion.

H1b: The higher the stimuli similarity, the higher the consumer confusion.

H1c: The higher the stimuli overload, the higher the consumer confusion.

According to Bijmolt et al. (1998), we argue that the quantitative overload is upstream of the antecedents that refer to qualitative stimuli (i.e., ambiguity, similarity).

H2a: The higher the stimuli overload, the higher the stimuli ambiguity.

H2b: The higher the stimuli overload, the higher the stimuli similarity.

Since sponsorship aims at influencing brand awareness (Johar and Pham 1999), the following hypotheses link consumer confusion with this outcome (Mitchell and Papavassiliou 1999).

H3a: The higher the consumer confusion, the less the correct classification (recall) of sponsoring brands as sponsors.

H3b: The higher the consumer confusion, the higher the misclassification of ambushing brands as sponsors.

Besides multiple sponsorships and ambusher activities, danger of mix-ups exists with regard to brands that have been sponsors of similar events. In such situations, retrieval of the correct sponsor is more difficult (Cornwell et al. 2006). We suppose that due to carryover effects the ‘other-event sponsors’ are perceived as being official sponsors.

H3c: The higher the consumer confusion, the higher the misclassification of other-event sponsors as sponsors.

In addition to memory interference, research shows that consumers feel annoyed by confusion (Dalakas et al. 2004). Annoyance, in turn, is likelyto influence the attitude toward the company’s sponsorship activities.

H4: The higher the consumer confusion, the more negative the attitude toward the sponsorship.

A further reaction could be opposite buying behavior to punish companies using the event for their communication (Séguin and O’Reilly 2008). Such opposite behavior might be expressed by so-called reactant behavioral intentions(Brehm and Brehm 1981).

H5: The higher the consumer confusion, the stronger the reactant behavioral intention.

Furthermore, research indicates that attitude toward sponsorship positively affects the purchase of sponsors’ products (Madrigal 2001). Hence, negative attitudes should lead to reactant intentions.

H6: The more negative the attitude toward the sponsorship, the stronger the reactant behavioral intentions.

To test thenew conceptualization,465 German participants completed an online survey during UEFA EURO 2008 (M = 25.4 years, 44.3% female). We measured confusion, overload, ambiguity, andsimilarity with items generated by two focus group discussions and two quantitative pretests. Measuringattitude toward the sponsorshipand reactant intentions, we modified existing scales(Hong and Page 1989; MacKenzie and Lutz 1989).Awareness was measured by aided recall. The list for this task included 11 main sponsors (42.45% correctly identified as sponsors), 11 ambushers (93.0% correctly rejected as sponsors), 4 brands that were sponsors of the FIFA Soccer World Cup 2006 (89.5% rejected), and 5 foils (96.4% rejected). That the five foils were detected as non-sponsors by almost all respondents implies that respondents were not lead astray.

Using structural equation modeling(LISREL 8) to test the hypotheses, the measurement models exhibithigh reliability, convergent and discriminant validity (Fornell and Larcker 1981). Fit indexes (χ²(181) = 457.74, p < .01; RMSEA = .057; CFI = .97, and NNFI = .96) suggest that the hypothesized model fits the data well.

All but two hypotheses are supported. Consumer confusion is influenced by ambiguity(H1a; .56), but not similarity(H1b; .05) and overload (H1c; .08). Perceived stimuli overload impactsonboth ambiguity(H2a; .38) and similarity(H2b; .68). Consumer confusion reduces memory for sponsors (H3a; -.41) and increases the likelihood that ambushers (H3b; .10) and other-event sponsors (H3c; .11) are perceived as official sponsors. Furthermore, confused consumers have a worseattitude toward the sponsorship engagement (H4; -.13) and show reactant intentions (H5; .15). Reactant intentions are higher the more negative the attitude toward the sponsorship (H6; -.43).

Concluding, we show that confused consumers have less memory of sponsors and are more likely to perceive ambushers and sponsors of other events as official sponsors. The most influential antecedent of consumer confusion is perceived stimuli ambiguity, which in turn is influenced by perceived stimuli overload. Thus, it is the combination of multiple sponsorships and ambusher activities that confuses consumers. Furthermore, we provide evidence that high levels of confusion negatively impact on the attitude toward the sponsorship and evoke reactant intentions. Ironically, this effect particularly impactsboth sponsors and ambushers which were successful in linking their companies or brands to the event.

References

Bijmolt, Tammo H. A., Michel Wedel, Rik G. M. Pieters, and Wayne S. DeSarbo (1998), “Judgments of Brand Similarity,” International Journal of Research in Marketing, 15(3), 249–68.

Brehm, Sharon S. and Jack W. Brehm (1981), Psychological Reactance: A Theory of Freedom and Control, New York, NY: Academic Press.

Cornwell, T. Bettina, Michael S. Humphreys, Angela M. Maguire, Clinton S. Weeks, and Cassandra L. Tellegen (2006), “Sponsorship-Linked Marketing: The Role of Articulation in Memory,” Journal of Consumer Research, 33(December), 312–21.

, George E. Relyea, Richard L. Irwin, and Isabelle Maignan (2000), “Understanding Long-Term Effects of Sports Sponsorship: Role of Experience, Involvement, Enthusiasm and Clutter,” International Journal of Sports Marketing & Sponsorship, 2 (2), 127–44.

Dalakas, Vassilis, Robert Madrigal, and Rick Burton (2004), “Understanding Ambush Marketing: Implications of Information Processing,” in Sports Marketing and the Psychology of Marketing Communication, eds.Lynn R. Kahle and Chris Riley, Mahwah, NJ: Lawrence Erlbaum Associates, 293–304.

Fornell, Claes and David F. Larcker (1981), “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error,” Journal of Marketing Research, 18 (February), 39–50.

Hong, Sung-mook and Sandra Page (1989), “A Psychological Reactance Scale: Development, Factor Structure and Reliability,” Psychological Reports, 64 (2), 1323–26.

Johar, Gita V. and Michel T. Pham (1999), “Relatedness, Prominence, and Constructive Sponsor Identification,” Journal of Marketing Research, 36 (August), 299–312.

MacKenzie, Scott B. and Richard J. Lutz (1989), “An Empirical Examination of the Structural Antecedents of Attitude toward the Ad in an Advertising Pretesting Context,” Journal of Marketing, 53 (April), 48–65.

Madrigal, Robert (2001), “Social Identity Effects in a Belief-Attitude-Intentions Hierarchy: Implications for Corporate Sponsorship,” Psychology & Marketing, 18 (2), 145–65.

Mitchell, Vincent-Wayne andVassilios Papavassiliou (1999), “Marketing Causes and Implications of Consumer Confusion,” Journal of Product & Brand Management, 8 (4), 319–39.

, Gianfranco Walsh, and Mo Yamin (2005), “Toward a Conceptual Model of Consumer Confusion,” in Advances in Consumer Research, Vol. 32, eds. Geeta Menon and Akshay R. Rao, Duluth, MN: Association for Consumer Research, 143–50.

Séguin, Benoitand Norm O’Reilly (2008), “The Olympic Brand, Ambush Marketing and Clutter,” International Journal of Sport Management and Marketing, 4 (1), 62–84.

Turnbull, Peter W., Sheena Leek, and Grace Ying (2000), “Customer Confusion: The Mobile Phone Market,” Journal of Marketing Management, 16 (1–3), 143–63.

1